Samples Selection for Artificial Neural Network Training in Preliminary Structural Design

An artificial neural network (ANN) is applied in the preliminary structural design of reticulated shells. Major efforts are made to enhance the generalization ability of networks through well-selected training samples. Number-theoretic methods (NTMs) are adopted to generate samples with low discrepancy, i.e.uniformly scattered in the domain, where discrepancy is a quantitative measurement of the uniformity. The discrepancy of the NTM-based sample set is 1/6-1/7 that of samples with equal spacing. In a case study,networks trained by NTM-based samples are compared with those trained by equal-spaced samples in generalizing performance. The results show that both the computational precision and stability of the former ANNs are more satisfactory than those of the latter. It is concluded that the flexibility of ANNs in generalizing can be effectively increased by use of uniformly distributed training samples rather than simply piling data.More reliable uniformity should be obtained, however, through NTMs instead of equal-spaced samples.     

含镍废水的隔膜电解法回收工艺研究

以含有一定浓度硼酸的含镍电镀废水作为阴极液,2％的NaOH水溶液为阳极液,阴离子交换膜为隔膜材料组成隔膜电解装置,对含镍电镀废水进行了回收工艺研究。考察了电解时间、电流密度、pH值、温度及硼酸浓度对镍回收率的影响。结果表明,延长反应时间、提高电解温度、增加硼酸浓度有利于提高回收率。在电流密度为300 A／m2,pH=4,温度为35℃,硼酸浓度为25 g／L的最佳工艺条件下电解6 h,镍的回收率高达96.64％,所得镍为松枝状结构电解镍,纯度为94.69％。     

基于油水分离的ZSM-5分子筛/石英复合材料的制备研究

该文采用TEOS(正硅酸四乙酯)、Al₂(SO₄)₃·18H₂O为原料,以TPAOH为模板剂,配制ZSM-5分子筛合成液,再以石英棉为载体,改变预处理条件与反应条件,合成ZSM-5分子筛/石英棉复合材料。通过XRD、红外光谱、SEM对产物进行表征,探究分子筛的生长情况。通过油水分离实验,探究ZSM-5分子筛/石英棉复合材料的吸附性能与最适宜的油水比例。在油水质量比例为1∶1时,2%NaOH预处理石英棉后合成的ZSM-5石英棉复合材料的吸附性能最好,油水分离效率达95.92%。